Experience: 8-10 years

Location: Pune

Role Overview:

Own the end-to-end technical design and implementation of enterprise-grade AI solutions. The role requires broad technical depth across application, hardware, platform, infrastructure, networking, security, scalability, and customer requirements, with robust leadership and solution-design capabilities.

Key Responsibilities:

- Ability to co-work with Agentic AI model, Optimizing processes agnatically [agentic optimizing engineering]
- Own end-to-end technical architecture and implementation of AI-based systems
- Design solutions across application, hardware, platform, network, infrastructure, and other relevant tiers
- Perform capacity planning and build reference architectures
- Make architecture and technology decisions and evaluate trade-offs
- Coordinate with infrastructure engineers, Field/Deployment Engineers, ML Engineers, CSI/Cluster Administrators, developers, and other technical roles
- Collaborate closely with customers to understand business and technical problems and translate them into enterprise-grade solutions
- Identify functional and non-functional requirements, including requirements that may not be explicitly stated by the customer
- Assess existing technical debt and understand the current environment before designing the target solution
- Conduct Proofs of Technology (POTs) and Proofs of Concept (POCs) where technology compatibility or suitability needs to be validated




- Evaluate compatibility across multiple technology stacks
- Design solutions considering enterprise-grade parameters such as security, scalability, reliability, and other relevant quality attributes
- Guide technical teams and provide architectural direction throughout implementation
- Must be available for on-call support as needed
- Ability to collaborate effectively with Agentic AI models
- Capability to optimize repetitive processes and workflows using agentic/autonomous engineering approaches

Required Skills:

- Strong enterprise AI solution architecture experience
- Broad understanding across AI applications, infrastructure, platforms, hardware, networking, and deployment environments
- Strong capacity planning and reference-architecture skills
- Experience with POCs/POTs and technology evaluation
- Strong understanding of enterprise-grade security, scalability, and reliability requirements
- Ability to understand technical debt and existing architecture before proposing changes
- Strong customer-facing and stakeholder-management capabilities
- Ability to coordinate and technically guide multiple engineering disciplines

Preferred Experience:

- Experience leading or coordinating multiple engineering teams
- Experience designing enterprise-grade AI platforms and solutions
- Exposure to complex customer environments and technology stacks

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